Answer: Unsupervised learning involves training a model to learn from the data itself, while supervised learning involves training a model using explicit guidance from a human.

## Explanation **Correct Answer: C** Unsupervised learning involves training a model to discover data patterns without explicit guidance, while supervised learning involves training a model to make predictions or classify data using labeled examples. ### Why other options are incorrect: **A is incorrect:** This reverses the definitions. Unsupervised learning actually involves training on unlabeled data, while supervised learning uses labeled data. **B is incorrect:** Unsupervised learning recognizes data patterns without an explicit/predefined target, not necessarily to "classify" - that's typically a supervised task. Unsupervised learning may involve clustering or dimensionality reduction. **D is incorrect:** This describes reinforcement learning (maximizing reward signal) versus supervised learning (minimizing loss function), not the distinction between unsupervised and supervised learning. ### Key Differences: - **Supervised Learning:** Uses labeled training data with known outcomes to make predictions - **Unsupervised Learning:** Discovers hidden patterns and structures in unlabeled data without predefined targets

Author: Tanishq Prabhu